Reproducibility Companion Paper: Knowledge Enhanced Neural Fashion Trend Forecasting

Hong-Han Shuai; Jinyoung Moon; Lizi Liao; Tat-Seng Chua; Wai Keung Wong; Xun Yang; Yujuan Ding; Yunshan Ma

arxiv: 2105.11826 · v1 · pith:NQDXXSRV · submitted 2021-05-25 · cs.LG · cs.IR· cs.MM

Reproducibility Companion Paper: Knowledge Enhanced Neural Fashion Trend Forecasting

Yunshan Ma , Yujuan Ding , Xun Yang , Lizi Liao , Wai Keung Wong , Tat-Seng Chua , Jinyoung Moon , Hong-Han Shuai This is my paper

Reviewed by Pith T0 review T1 audit T2 compute T3 formal T4 reserved pith:NQDXXSRV record.json open to challenge →

classification cs.LG cs.IRcs.MM

keywords experimentsreplicationartifactcompanionenhancedfashionforecastingknowledge

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This companion paper supports the replication of the fashion trend forecasting experiments with the KERN (Knowledge Enhanced Recurrent Network) method that we presented in the ICMR 2020. We provide an artifact that allows the replication of the experiments using a Python implementation. The artifact is easy to deploy with simple installation, training and evaluation. We reproduce the experiments conducted in the original paper and obtain similar performance as previously reported. The replication results of the experiments support the main claims in the original paper.

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Reproducibility Companion Paper: Knowledge Enhanced Neural Fashion Trend Forecasting

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